M5 Model Trees and Neural Networks: Application to Flood Forecasting in the Upper Reach of the Huai River in China-Reference-Cited by-同舟云学术

M5 Model Trees and Neural Networks: Application to Flood Forecasting in the Upper Reach of the Huai River in China

Published:2004-11 Issue:6 Volume:9 Page:491-501
ISSN:1084-0699
Container-title:Journal of Hydrologic Engineering
language:en
Short-container-title:J. Hydrol. Eng.

Author:

Solomatine Dimitri P.¹,Xue Yunpeng²

Affiliation:

1. Associate Professor, UNESCO-IHE Institute for Water Education (IHE Delft), P.O. Box 3015, 2601 DA Delft, The Netherlands. (corresponding author). E-mail: sol@ihe.nl

2. Yellow River Conservancy Commission, 11 Jinshui Rd., 450003 Zhengzhou, China. E-mail: ypxue@yellowriver.gov.cn

Publisher

American Society of Civil Engineers (ASCE)

Subject

General Environmental Science,Water Science and Technology,Civil and Structural Engineering,Environmental Chemistry

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%291084-0699%282004%299%3A6%28491%29

Reference27 articles.

1. Investigating the role of saliency analysis with a neural network rainfall-runoff model

2. Nonlinear flood routing with multilinear models

3. Bhattacharya B. and Solomatine D.P. ( 2002a). “Application of artificial neural network in reconstructing stage-discharge relationship.” Proc. 4th Int. Conf. on Hydroinformatics Iowa.

4. Bhattacharya B. and Solomatine D.P. ( 2002b). “Application of artificial neural networks and M5 model trees to modelling stage-discharge relationship.” Proc. 2nd Int. Symp. on Flood Defence Beijing. B. S. Wu Z. Y. Wang G. Q. Wang G. H. Huang H. W. Fang and J. C. Huang eds. Science Press New York.

5. Performance of Neural Networks in Daily Streamflow Forecasting

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